This state-of-the-art book offers cutting-edge optimization techniques and practical decision-making frameworks essential for enhancing the efficiency and reliability of sustainable energy systems, making it an invaluable resource for researchers, policymakers, and energy professionals.
Optimization in Sustainable Energy: Methods and Applications brings together valuable knowledge, methods, and practical examples to help scholars, researchers, professionals, and policymakers address the growing challenges of optimizing sustainable energy. This volume covers a range of topics, including mathematical models, heuristic algorithms, renewable resource management, and energy storage optimization. Each chapter explores a different aspect of sustainable energy, providing both theoretical understanding and practical guidance.
The volume explores challenges and opportunities surrounding the integration of multi-criteria decision-making techniques in energy planning, highlighting insights on environmental, economic, and social factors influencing the strategic allocation of resources. The use of evolutionary algorithms, machine learning, and metaheuristics to optimize energy storage, distribution, and optimization are also discussed.
The transition towards sustainable energy is at the forefront of global priorities, driven by the urgent need to mitigate climate change, reduce carbon emissions, and enhance energy security. As countries and industries increasingly prioritize renewable sources like wind, solar, and hydroelectric power, the complexity of optimizing these systems becomes a critical challenge. Optimization in Sustainable Energy: Methods and Applications, is a comprehensive exploration of cutting-edge methodologies used to enhance the efficiency, reliability, and performance of sustainable energy systems.
Audience
Research scholars, academics, students, policymakers, and industry experts in mechanical engineering, electrical engineering, and energy science.
Preface xvii
Acknowledgment xxi
Part I: Multi-Criteria Optimization and Strategic Planning in Sustainable
Energy 1
1 Strategic Roadmap for Turkey's Sustainable Energy Transition: A
Multi-Criteria Perspective 3
Gülay Demir and Prasenjit Chatterjee
1.1 Introduction 4
1.2 Literature Review 6
1.3 Methodology for Research 8
1.4 Results 14
1.5 Discussion, Practical and Managerial Implications 21
1.6 Conclusions, Limitations, and Future Directions 21
2 A Novel p, q-Quasirung Orthopair Fuzzy Group Decision-Making Framework for
Selection of Renewable Energy Sources 27
Sanjib Biswas, Gülay Demir and Prasenjit Chatterjee
2.1 Introduction 28
2.2 Literature Review 30
2.3 Preliminary Concepts: p, q-QOFS 32
2.4 Fairly Operations and p, q-QOFS Weighted Fairly Aggregation 35
2.5 Materials and Methods 42
2.6 Findings 50
2.7 Discussions 56
2.8 Conclusion and Future Scope 58
3 Evaluating Carbon Footprint Reduction Strategies: A Fuzzy Multi-Criteria
Decision-Making Approach 69
Gülay Demir and Prasenjit Chatterjee
3.1 Introduction 70
3.2 Literature Review 78
3.3 Research Methodology 81
3.4 Case Study 87
3.5 Insights, Applications, and Managerial Implications 105
3.6 Conclusions, Limitations, and Future Directions 108
4 Prioritizing Sustainable Energy Strategies Using Multi-Criteria
Decision-Making Models in Type-2 Neutrosophic Environment 113
Ömer Faruk Görcün, Hande Kücükönder and Ahmet Calik
4.1 Introduction 114
4.2 The Research Background 116
4.3 The Suggested Model 129
4.4 Implementing the Model to Identify the Best Sustainable Energy Strategy
142
4.5 Results and Discussions 167
4.6 Conclusions and Future Research Direction 171
5 ENTROPY-Based Evaluation of Global Renewable Energy Trends 183
Rahim Arslan
5.1 Introduction 183
5.2 Renewable Energy Concepts 185
5.3 World Countries and Türkiye in Clean Energy 187
5.4 Evaluation of Renewable Energy Resources Using MCDM Methods 189
5.5 ENTROPY Method 189
5.6 Case Study 192
5.7 Conclusions 204
Part II: Optimization Techniques in Sustainable Energy 207
6 Optimization in Sustainable Energy: A Bibliometric Analysis 209
Rajeev Ranjan, Sonu Rajak, Prasenjit Chatterjee and Divesh Chauhan
6.1 Introduction 210
6.2 Optimization in Sustainable Energy 212
6.3 Materials and Methods 217
6.4 The Optimization Results in Sustainable Energy by Bibliometric Analysis
219
6.5 Discussions 233
6.6 Conclusions 235
7 A Novel Optimization-Based Cooling System for Improving Efficacy of Solar
Panels Under Changing Climatic Conditions 241
J. Sivakumar, A. G. Karthikeyan, R. Karthikeyan and R. Girimurugan
7.1 Introduction 242
7.2 Solar PV 242
7.3 Hybrid PV Panel 247
7.4 Optimization 248
7.5 Conventional Optimization Approaches 249
7.6 Proposed Optimization Algorithm 258
7.7 Conclusion 260
8 Multi-Objective Optimization in Sustainable Energy 267
Sevtap Tirink
8.1 Introduction 268
8.2 Sustainable Development and Energy Sustainability 269
8.3 Sustainable Energy System Models 271
8.4 Foundations of Multi-Objective Optimization 276
8.5 Challenges and Future Directions in Multi-Objective Optimization for
Sustainable Energy 281
8.6 Conclusions 282
9 Data Analytics for Performance Optimization in Renewable Energy 291
Aparna Unni and Harpreet Kaur Channi
9.1 Introduction 292
9.2 Literature Review 294
9.3 Renewable Energy Technologies 296
9.4 Statistical Modeling 300
9.5 Methodology 302
9.6 Challenges and Opportunities 305
9.7 Application Areas of Data Analytics in Renewable Energy 309
9.8 Real-Time Implementation Using PVsyst 314
9.9 Top World-Level Case Studies 316
9.10 Conclusion 323
10 Integration of Smart Grids in Energy Optimization 329
Harpreet Kaur Channi, Ramandeep Sandhu and Aayush Anand
10.1 Introduction 330
10.2 Smart Grid Fundamentals 333
10.3 Demand-Side Management 337
10.4 Data Analytics in Smart Grid 341
10.5 Smart Grid Deployment Worldwide 346
10.6 Conclusion 352
11 Markov Model-Based Reliability Evaluation of Multiport Converter Fed
Induction Motor Drive for Electric Vehicle Applications 357
Manas Taneja and Dheeraj Joshi
11.1 Introduction 357
11.2 Markovs Modeling 359
11.3 Thermal Model 361
11.4 Transition Rate Evaluation 362
11.5 Genetic Algorithm 364
11.6 Reliability Calculations 365
11.7 Conclusion 369
12 Forecasting Wind Energy Produced from Wind Turbine: A Markov Chain-Based
Approach 373
Yasin Atci and Sibel Atan
12.1 Introduction 373
12.2 Literature Review 375
12.3 Wind Energy 376
12.4 Markov Processes 383
12.5 Wind Energy Forecasting with Markov Chains 388
12.6 Conclusions and Recommendations 399
13 Efficient Optimization Techniques for Renewable and Sustainable Energy
Systems 405
Swati Sharma and Ikbal Ali
13.1 Introduction 406
13.2 Renewable Energy Approaches: An Introductory Overview 407
13.3 Efficiency Unbound: Unconstrained Optimization Techniques for Renewable
Energy Systems 420
13.4 Enhancing Renewable Energy Efficiency: Constrained Optimization Methods
433
13.5 Conclusions and Discussion 455
14 Energy Optimization: Challenges, Issues, and Role of Machine Learning
Techniques 465
Anshuka Bansal, Ashwani Kumar Aggarwal and Anita Khosla
14.1 Introduction 466
14.2 Challenges in Energy Optimization 468
14.3 Energy Optimization Methods 470
14.4 Role of Machine Learning Methods 473
14.5 Machine Learning Models 475
14.6 Conclusions 478
References 479
Index 487
Prasenjit Chatterjee, PhD, is a professor and the Dean of Research and Consultancy at the MCKV Institute of Engineering. He has published 135 research papers and 43 books and serves as a lead series editor for several international book series. He is known for his work developing the MARCOS and RAFSI decision-making methods. His research interests include energy optimization, intelligent decision-making, fuzzy computing, sustainability modeling, and supply chain management.
Anita Khosla, PhD, is a professor at Manav Rachna International Institute of Research and Studies with over 27 years of teaching experience. She has published three books and over 50 papers in international journals and conferences and served as a speaker and organizer for numerous conferences and seminars. She is known for her coordination in establishing the Factory Automation Lab in conjunction with Mitsubishi Electric India.
Ashwani Kumar, PhD, is an associate professor in the Department of Electrical and Instrumentation Engineering at the Sant Longowal Institute of Engineering and Technology, Longowal, India with over 26 years of experience. He has over 70 publications in book chapters and international journals and conferences. He is the recipient of the Monbukagakusho and Quality Improvement Programme scholarships. His research interests include computer vision, artificial intelligence, and remote sensing.
Gülay Demir, PhD, is an associate professor at the School of Health Services at Sivas Cumhuriyet University with over 10 years of academic experience. She is the author of three books and 50 scientific articles, and the editor of two books. Her research interests include smart grids, renewable energy, and fuzzy logic.
